{"data":{"id":"19cd16b9-856a-456f-914d-d7ebbe3267d3","title":"Improving Viewpoint Robustness for Visual Recognition via Adversarial Training","summary":"Visual recognition systems struggle when objects are viewed from different angles, even though the object hasn't changed. This paper proposes Viewpoint-Invariant Adversarial Training (VIAT), which treats different viewing angles as attacks and trains AI models to handle them better by learning from a distribution of challenging viewpoints. The researchers also created new datasets and evaluation methods to measure how well vision models can handle viewpoint changes.","solution":"N/A -- no mitigation discussed in source.","labels":["research","safety"],"sourceUrl":"http://ieeexplore.ieee.org/document/11570071","publishedAt":"2026-06-18T13:16:23.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-06-18T13:16:23.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["safety"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}